The institution establishes an interoperability framework to formalize a systematic and standardized approach to the implementation of integrated social security systems.
The framework covers all levels of the organization and specifies the political and legal context, the business processes and concepts involved in interoperability operations, and the technologies used to implement them.
This section of the guidelines provides a high-level reference point for social security institutions applying interoperability techniques. The six guidelines which follow form a starting point from which institutions can develop their own policies and plans, and will assist in addressing the challenges of interoperability through a consistent and standards-based approach. The guidelines canvass the five dimensions of interoperability: political, legal, organizational, semantic and technical. The specific guidelines in this section are:
The following guidelines are organized in three sections:
Section B.1, Interoperability, focuses on implementing integrated ICT systems by ensuring the interoperability of the social security institution’s own systems with independent ICT-based systems.
Section B.2, Data Security and Privacy, addresses the issues of providing data security and protecting data privacy when integrating data from social programmes.
The institution implements effective and efficient mechanisms for information retrieval and analysis which provide the means to exploit existing data assets, especially to support decision-making.
The effectiveness and efficiency of processes using information will, therefore, strongly depend on the mechanisms to retrieve and analyse the information.
The institution carries out unified and formalized data quality management, enabling it to improve the reliability of data and information used in the institution and, therefore, confidence in related processes.
As data is a key asset for social security operations, managing its quality becomes a required activity. The goal of data quality management is to formally and rigorously manage the data quality attributes that are relevant in social security operations.
The institution carries out data development and operation activities in a systematic and consistent way.
Data development concerns the analysis, design, implementation, deployment and maintenance of data and information systems. Data operations, which involve database and data technology administration, aim at managing the availability of data throughout its life cycle, optimizing the performance of database operations and protecting the integrity of data assets.
The institution develops a unique master data model, which standardizes the definition of the core objects and relationships (e.g. persons, employers, enrolment periods, benefits). A corresponding ICT-based master data system fosters the consistency of such information.
The institution establishes a data governance framework to formalize the exercise of authority and control (planning, monitoring and enforcement) over the management of data assets.
The data governance function guides how all other data management functions are performed.
Data and information are fundamental assets for social security institutions. The scale of social security institutions and relevance of the activities they develop increase the complexity of and risks related to data management. Institutions make key decisions based on data and information about people, including employees, employers and work activities.
The institution permanently monitors, analyses and treats ICT-related events and problems in order to prevent incidents. In turn, incidents are managed in order to restore normal services as quickly as possible and minimize the adverse impact on business operations.
